{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T17:15:34Z","timestamp":1771521334056,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T00:00:00Z","timestamp":1471305600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"national key research and development program","doi-asserted-by":"publisher","award":["2016YFC0803101"],"award-info":[{"award-number":["2016YFC0803101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"key laboratory of watershed ecology and geographical environment monitoring, National Administration of Surveying, Mapping and Geoinformation","award":["WE2016005"],"award-info":[{"award-number":["WE2016005"]}]},{"DOI":"10.13039\/501100001809","name":"national natural science foundation of China","doi-asserted-by":"publisher","award":["41004003"],"award-info":[{"award-number":["41004003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"natural science foundation of Jiangsu province, China","award":["BE2016701"],"award-info":[{"award-number":["BE2016701"]}]},{"name":"natural science foundation of Lianyungang city, China","award":["SH1506"],"award-info":[{"award-number":["SH1506"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Previous studies have demonstrated that non-Euclidean distance metrics can improve model fit in the geographically weighted regression (GWR) model. However, the GWR model often considers spatial nonstationarity and does not address variations in local temporal issues. Therefore, this paper explores a geographically temporal weighted regression (GTWR) approach that accounts for both spatial and temporal nonstationarity simultaneously to estimate house prices based on travel time distance metrics. Using house price data collected between 1980 and 2016, the house price response and explanatory variables are then modeled using both the GWR and the GTWR approaches. Comparing the GWR model with Euclidean and travel distance metrics, the GTWR model with travel distance obtains the highest value for the coefficient of determination (     R 2     ) and the lowest values for the Akaike information criterion (AIC). The results show that the GTWR model provides a relatively high goodness of fit and sufficient space-time explanatory power with non-Euclidean distance metrics. The results of this study can be used to formulate more effective policies for real estate management.<\/jats:p>","DOI":"10.3390\/e18080303","type":"journal-article","created":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T10:03:21Z","timestamp":1471341801000},"page":"303","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["A Geographically Temporal Weighted Regression Approach with Travel Distance for House Price Estimation"],"prefix":"10.3390","volume":"18","author":[{"given":"Jiping","family":"Liu","sequence":"first","affiliation":[{"name":"Research Center of Government GIS, Chinese Academy of Surveying and Mapping, No. 28 Lianhuachi West Road, Haidian District, Beijing 100830, China"}]},{"given":"Yi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Resource and Environmental Science, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Shenghua","family":"Xu","sequence":"additional","affiliation":[{"name":"Research Center of Government GIS, Chinese Academy of Surveying and Mapping, No. 28 Lianhuachi West Road, Haidian District, Beijing 100830, China"}]},{"given":"Yangyang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Center of Government GIS, Chinese Academy of Surveying and Mapping, No. 28 Lianhuachi West Road, Haidian District, Beijing 100830, China"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Research Center of Government GIS, Chinese Academy of Surveying and Mapping, No. 28 Lianhuachi West Road, Haidian District, Beijing 100830, China"}]},{"given":"Fuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Research Center of Government GIS, Chinese Academy of Surveying and Mapping, No. 28 Lianhuachi West Road, Haidian District, Beijing 100830, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,8,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A computer movie simulating urban growth in the Detroit region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2751","DOI":"10.1068\/a38218","article-title":"Spatial-filtering based contributions to a critique of geographically weighted regression (GWR)","volume":"40","author":"Griffith","year":"2008","journal-title":"Environ. Plan. A"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1111\/j.1538-4632.1996.tb00936.x","article-title":"Geographically weighted regression: A method for exploring spatial nonstationarity","volume":"28","author":"Brunsdon","year":"1996","journal-title":"Geogr. Anal."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1007\/s10109-007-0051-3","article-title":"A systematic investigation of cross-validation in GWR model estimation: Empirical analysis and Monte Carlo simulations","volume":"9","author":"Farber","year":"2007","journal-title":"J. Geogr. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10109-006-0028-7","article-title":"Incorporating spatial variation in housing attribute prices: A comparison of geographically weighted regression and the spatial expansion method","volume":"9","author":"Bitter","year":"2007","journal-title":"J. Geogr. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1016\/j.econmod.2012.08.015","article-title":"On the estimation and testing of mixed geographically weighted regression models","volume":"29","author":"Wei","year":"2012","journal-title":"Econ. Modell."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1177\/0042098013492234","article-title":"Spatial heterogeneity in hedonic house price models: The case of Austria","volume":"51","author":"Helbich","year":"2014","journal-title":"Urban Stud."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.proenv.2011.07.017","article-title":"Geographically weighted regression using a non-euclidean distance metric with a study on London house price data","volume":"7","author":"Lu","year":"2011","journal-title":"Procedia Environ. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1080\/13658816.2013.865739","article-title":"Geographically weighted regression with a non-euclidean distance metric: A case study using hedonic house price data","volume":"28","author":"Lu","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_10","unstructured":"Mcmillen, D.P., and Redfearn, C.L. Estimation, Interpretation, and Hypothesis Testing for Nonparametric Hedonic House Price Functions. Available online: http:\/\/lusk.usc.edu\/sites\/default\/files\/working_papers\/wp_2007-1007.pdf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1111\/j.1467-9787.2010.00664.x","article-title":"Estimation and hypothesis testing for nonparametric hedonic house price functions","volume":"50","author":"Mcmillen","year":"2010","journal-title":"J. Reg. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"262","DOI":"10.3390\/rs8030262","article-title":"A geographically and temporally weighted regression model for ground-level PM2.5 estimation from satellite-derived 500 m resolution AOD","volume":"8","author":"Bai","year":"2016","journal-title":"Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1080\/13658810802672469","article-title":"Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices","volume":"24","author":"Huang","year":"2010","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.regsciurbeco.2013.10.005","article-title":"Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change","volume":"44","author":"Wrenn","year":"2014","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_15","unstructured":"Griffith, D.A. (1987). Spatial Autocorrelation: A Primer, Assn of Amer Geographers."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1080\/13658816.2013.878463","article-title":"A geographically and temporally weighted autoregressive model with application to housing prices","volume":"28","author":"Wu","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1111\/j.1467-9787.2010.00694.x","article-title":"If Alonso was right: Modeling accessibility and explaining the residential land gradient","volume":"51","author":"Ahlfeldt","year":"2011","journal-title":"J. Reg. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Apparicio, P., Abdelmajid, M., Riva, M., and Shearmur, R. (2008). Comparing alternative approaches to measuring the geographical accessibility of urban health services: Distance types and aggregation-error issues. Int J. Health Geogr., 7.","DOI":"10.1186\/1476-072X-7-7"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/j.apgeog.2008.12.003","article-title":"Measuring spatial accessibility to primary care in rural areas: Improving the effectiveness of the two-step floating catchment area method","volume":"29","author":"Mcgrail","year":"2009","journal-title":"Appl. Geogr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1111\/j.1541-0064.2009.00301.x","article-title":"Measuring potential spatial access to primary health care physicians using a modified gravity model","volume":"54","author":"Schuurman","year":"2010","journal-title":"Can. Geogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.apgeog.2012.12.003","article-title":"Estimating the effect of turn penalties and traffic congestion on measuring spatial accessibility to primary health care","volume":"39","author":"Yiannakoulias","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1080\/13658816.2015.1087001","article-title":"The Minkowski approach for choosing the distance metric in geographically weighted regression","volume":"30","author":"Lu","year":"2015","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2843","DOI":"10.1016\/j.eswa.2008.01.044","article-title":"Determinants of house prices in Turkey: Hedonic regression versus artificial neural network","volume":"36","author":"Selim","year":"2009","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.regsciurbeco.2008.11.001","article-title":"How informative are average effects? Hedonic regression and amenity capitalization in complex urban housing markets","volume":"39","author":"Redfearn","year":"2009","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1080\/10835547.2009.12091245","article-title":"Neural network hedonic pricing models in mass real estate appraisal","volume":"31","author":"Peterson","year":"2009","journal-title":"J. R. Estate Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1565","DOI":"10.1177\/0042098008091491","article-title":"Moving window approaches for hedonic price estimation: An empirical comparison of modelling techniques","volume":"45","author":"Paez","year":"2008","journal-title":"Urban Stud."},{"key":"ref_27","first-page":"405","article-title":"A comparison of localized regression models in a hedonic house price context","volume":"29","author":"Farber","year":"2006","journal-title":"Can. J. Reg. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"65","DOI":"10.31671\/dogus.2019.223","article-title":"Determinants of house prices in turkey: A hedonic regression model","volume":"9","author":"Selim","year":"2008","journal-title":"Do\u011fu\u015f \u00dcniversitesi Dergisi"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1080\/10835547.2008.12091225","article-title":"An adaptive neuro-fuzzy inference system based approach to real estate property assessment","volume":"30","author":"Guan","year":"2008","journal-title":"J. R. Estate Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1016\/j.eswa.2009.07.031","article-title":"The use of fuzzy logic in predicting house selling price","volume":"37","author":"Aytekin","year":"2010","journal-title":"Expert Syst. Appl."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.regsciurbeco.2014.03.004","article-title":"The floor area ratio gradient: New York City, 1890\u20132009","volume":"48","author":"Barr","year":"2014","journal-title":"Reg. Sci. Urban Econ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1080\/02664763.2014.980789","article-title":"Collinearity: Revisiting the variance inflation factor in ridge regression","volume":"42","author":"Garcia","year":"2015","journal-title":"J. Appl. Stat."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s10109-005-0155-6","article-title":"Multicollinearity and correlation among local regression coefficients in geographically weighted regression","volume":"7","author":"Wheeler","year":"2005","journal-title":"J. Geogr. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2464","DOI":"10.1068\/a38325","article-title":"Diagnostic tools and a remedial method for collinearity in geographically weighted regression","volume":"39","author":"Wheeler","year":"2007","journal-title":"Environ. Plan. A"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2992","DOI":"10.1068\/a44111","article-title":"A simulation-based study of geographically weighted regression as a method for investigating spatially varying relationships","volume":"43","author":"Farber","year":"2011","journal-title":"Environ. Plan. A"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"273","DOI":"10.2747\/1548-1603.46.3.273","article-title":"Extreme coefficients in geographically weighted regression and their effects on mapping","volume":"46","author":"Cho","year":"2009","journal-title":"GIsci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1111\/tgis.12020","article-title":"Using contextualized geographically weighted regression to model the spatial heterogeneity of land prices in Beijing, China","volume":"17","author":"Harris","year":"2013","journal-title":"Trans. GIS"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1007\/s11004-006-9055-7","article-title":"On the use of non-euclidean distance measures in geostatistics","volume":"38","author":"Curriero","year":"2007","journal-title":"Math. Geol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1068\/a3162","article-title":"Statistical tests for spatial nonstationarity based on the geographically weighted regression model","volume":"32","author":"Leung","year":"2000","journal-title":"Environ. Plan. A"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1111\/j.0002-9092.2004.600_2.x","article-title":"Geographically weighted regression: The analysis of spatially varying relationships","volume":"86","author":"Fotheringham","year":"2004","journal-title":"Am. J. Agric. Econ."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/18\/8\/303\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:28:28Z","timestamp":1760210908000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/18\/8\/303"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,16]]},"references-count":40,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2016,8]]}},"alternative-id":["e18080303"],"URL":"https:\/\/doi.org\/10.3390\/e18080303","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,16]]}}}